PhD Student |
Latest Publications
- Bridging the gap between machine learning and particle accelerator physics with high-speed, differentiable simulations: Jan Kaiser et al., Phys. Rev. Accel. Beams, doi: 10.1103/PhysRevAccelBeams.27.054601
- Large Language Models for Human-Machine Collaborative Particle Accelerator Tuning through Natural Language: Jan Kaiser et al., arXiv, doi: 10.48550/arXiv.2405.08888
- Learning to Do or Learning While Doing: Reinforcement Learning and Bayesian Optimisation for Online Continuous Tuning: Jan Kaiser et al., arXiv, doi: 10.48550/arXiv.2306.03739
- Machine learning for combined scalar and spectral longitudinal phase space reconstruction: Jan Kaiser et al., JACoW Publishing, doi: 10.18429/JACoW-IPAC2023-THPL019
- Application of Machine Learning in Longitudinal Phase Space Prediction at the European XFEL: Zihan Zhu et al., Proceedings of the 40th International Free Electron Laser Conference (FEL2022), doi: https://indico.jacow.org/event/44/contributions/545/